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Submodular set function
Known as:
Submodular
, Submodular function
In mathematics, a submodular set function (also known as a submodular function) is a set function whose value, informally, has the property that the…
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Active learning (machine learning)
Alexander Schrijver
Artificial intelligence
Automatic summarization
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Broader (1)
Combinatorial optimization
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2016
2016
Flowing with the water: On optimal monitoring of water distribution networks by mobile sensors
Rong Du
,
C. Fischione
,
Ming Xiao
IEEE INFOCOM - The 35th Annual IEEE…
2016
Corpus ID: 2537829
Contamination in drinkable water distribution networks can be potentially monitored by new and agile mobile sensor networks…
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2016
2016
Distributed Coverage Maximization via Sketching
M. Bateni
,
Hossein Esfandiari
,
V. Mirrokni
arXiv.org
2016
Corpus ID: 2762161
Coverage problems are central in optimization and have a wide range of applications in data mining and machine learning. While…
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2015
2015
Efficient Algorithms to Optimize Diffusion Processes under the Independent Cascade Model
Xiaojian Wu
,
D. Sheldon
,
S. Zilberstein
2015
Corpus ID: 11442185
We study scalable algorithms to optimize diffusion processes under the Independent Cascade model. We consider a broad class of…
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2012
2012
Combinatorial problems with submodular coupling in machine learning and computer vision
S. Jegelka
2012
Corpus ID: 459421
2012
2012
A Metric on Space of Measurable Functions and the Related convergence
Gang Li
Int. J. Uncertain. Fuzziness Knowl. Based Syst.
2012
Corpus ID: 2265385
A new metric is proposed on the space of measurable functions in the setting of non-additive measure theory. The convergence…
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2012
2012
Discrete Energy Minimization, beyond Submodularity: Applications and Approximations
Shai Bagon
arXiv.org
2012
Corpus ID: 26644496
In this thesis I explore challenging discrete energy minimization problems that arise mainly in the context of computer vision…
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2011
2011
A Fast Solver for Truncated-Convex Priors: Quantized-Convex Split Moves
Anna Jezierska
,
Hugues Talbot
,
Olga Veksler
,
Daniel Wȩsierski
Energy Minimization Methods in Computer Vision…
2011
Corpus ID: 15034997
This paper addresses the problem of minimizing multilabel energies with truncated convex priors. Such priors are known to be…
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Review
2010
Review
2010
Iterative Rounding and Relaxation
L. Lau
,
Mohit Singh
2010
Corpus ID: 10384978
In this survey paper we present an iterative method to analyze linear programming formulations for combinatorial optimization…
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2008
2008
LP-relaxation of Binarized Energy Minimization ( Version 1 . 50 )
A. Shekhovtsov
,
V. Kolmogorov
,
Pushmeet Kohli
,
C. Rother
,
Philip H. S. Torr
2008
Corpus ID: 15877184
We address the problem of energy minimization, which is (1) generally NP-complete and (2) involves many discrete variables…
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2008
2008
Which submodular functions are expressible using binary submodular functions
Stanislav Živný
2008
Corpus ID: 15169590
Submodular functions occur in many combinatorial optimisation problems and a number of polynomial-time algorithms have been…
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